A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf
.
MSeg: A Composite Dataset for Multi-Domain Semantic Segmentation
2020
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Input image Ground truth ADE20K model Mapillary model COCO model MSeg model Figure 1: MSeg unifies multiple semantic segmentation datasets by reconciling their taxonomies and resolving incompatible annotations. This enables training models that perform consistently across domains and generalize better. Input images in this figure were taken (top to bottom) from the ScanNet [8], WildDash [44], and Pascal VOC [10] datasets, none of which were seen during training.
doi:10.1109/cvpr42600.2020.00295
dblp:conf/cvpr/LambertLSHK20
fatcat:nxepr7qrwbgqzhcsuiqlp7c7oi